Search results for: mitigation techniques

Authors: N. Ould cherchali, M. S. Boucherit, L. Barazane, A. Morsli

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Photovoltaic power is widely used to supply isolated or unpopulated areas (lighting, pumping, etc.). Great advantage is that this source is inexhaustible, it offers great safety in use and it is clean. But the dynamic models used to describe a photovoltaic system are complicated and nonlinear and due to nonlinear I-V and P–V characteristics of photovoltaic generators, a maximum power point tracking technique (MPPT) is required to maximize the output power. In this paper, two online techniques of maximum power point tracking using robust controller for photovoltaic systems are proposed, the first technique use fuzzy logic controller (FLC) and the second use sliding mode controller (SMC) for photovoltaic systems. The two maximum power point tracking controllers receive the partial derivative of power as inputs, and the output is the duty cycle corresponding to maximum power. A Photovoltaic generator with Boost converter is developed using MATLAB/Simulink to verify the preferences of the proposed techniques. SMC technique provides a good tracking speed in fast changing irradiation and when the irradiation changes slowly or is constant the panel power of FLC technique presents a much smoother signal with less fluctuations.

Keywords: fuzzy logic controller, maximum power point, photovoltaic system, tracker, sliding mode controller

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Authors: Luiz Daniel Garay Trindade, Antonio De Freitas Valle Neto, Fabio Paulo Basso, Elder De Macedo Rodrigues, Maicon Bernardino, Daniel Welfer, Daniel Muller

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Agriculture plays an important role in society since it is one of the main sources of food in the world. To help the production and yield of crops, precision agriculture makes use of technologies aiming at improving productivity and quality of agricultural commodities. One of the problems hampering quality of agricultural production is the disease affecting crops. Failure in detecting diseases in a short period of time can result in small or big damages to production, causing financial losses to farmers. In order to provide a map of the contributions destined to the early detection of plant diseases and a comparison of the accuracy of the selected studies, a systematic literature review of the literature was performed, showing techniques for digital image processing and neural networks. We found 35 interesting tool support alternatives to detect disease in 19 plants. Our comparison of these studies resulted in an overall average accuracy of 87.45%, with two studies very closer to obtain 100%.

Keywords: pattern recognition, image processing, deep learning, precision agriculture, smart farming, agricultural automation

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Authors: Tarik Ouslimane, Abdenour Lami, Salaheddine Aoudj, Mouna Hecini, Ouahiba Bouchelaghem, Nadjib Drouiche

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Slurry waste is a byproduct generated from the slicing process of multi-crystalline silicon ingots. This waste can be used as a secondary resource to recover high purity silicon which has a great economic value. From the management perspective, the ever increasing generation of kerf slurry waste loss leads to significant challenges for the photovoltaic industry due to the current low use of slurry waste for silicon recovery. Slurry waste, in most cases, contains silicon, silicon carbide, metal fragments and mineral-oil-based or glycol-based slurry vehicle. As a result, of the global scarcity of high purity silicon supply, the high purity silicon content in slurry has increasingly attracted interest for research. This paper presents a critical overview of the current techniques employed for high purity silicon recovery from kerf slurry waste. Hydrometallurgy is continuously a matter of study and research. However, in this review paper, several new techniques about the process of high purity silicon recovery from slurry waste are introduced. The purpose of the information presented is to improve the development of a clean and effective recovery process of high purity silicon from slurry waste.

Keywords: Kerf-loss, slurry waste, silicon carbide, silicon recovery, photovoltaic, high purity silicon, polyethylen glycol

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Authors: Telesphore Tiendrebeogo, Oumarou Sié

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Cloud computing technologies have attracted considerable interest in recent years. Thus, these latters have become more important for many existing database applications. It provides a new mode of use and of offer of IT resources in general. Such resources can be used “on demand” by anybody who has access to the internet. Particularly, the Cloud platform provides an ease to use interface between providers and users, allow providers to develop and provide software and databases for users over locations. Currently, there are many Cloud platform providers support large scale database services. However, most of these only support simple keyword-based queries and can’t response complex query efficiently due to lack of efficient in multi-attribute index techniques. Existing Cloud platform providers seek to improve performance of indexing techniques for complex queries. In this paper, we define a new cloud computing architecture based on a Distributed Hash Table (DHT) and design a prototype system. Next, we perform and evaluate our cloud computing indexing structure based on a hyperbolic tree using virtual coordinates taken in the hyperbolic plane. We show through our experimental results that we compare with others clouds systems to show our solution ensures consistence and scalability for Cloud platform.

Keywords: virtual coordinates, cloud, hyperbolic plane, storage, scalability, consistency

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Authors: Pankaj Kumar

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Rapid global changes resulted in unfavorable hydrological, ecological, and environmental changes and cumulatively affected natural resources. As a result, the local communities become vulnerable to water stress, poor hygiene, the spread of diseases, food security, etc.. However, the central point for this vulnerability revolves around water resources and the way people interrelate with the hydrological system. Also, most of the efforts to minimize the adverse effect of global changes are centered on the mitigation side. Hence, countries with poor adaptive capacities and poor governance suffer most in case of disasters. However, several transdisciplinary numerical tools are well designed and are capable of answering “what-if questions” through scenario analysis using a system approach. This study has predicted the future water environment in Marikina River in the National Capital Region, Metro Manila of Philippines, using Water Evaluation and Planning (WEAP), an integrated water resource management tool. Obtained results can answer possible adaptation measures along with their associated uncertainties. It also highlighted various challenges for the policy planners to design adaptation countermeasures as well as to track the progress of achieving SDG 6.0.

Keywords: water quality, Philippines, climate change adaptation, hydrological simulation, wastewater management, weap

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Authors: Imine Zakaria, Meftah Sidi Mohamed El Amine

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One of the most vital aerodynamic organs of a flying machine is the wing, which allows it to fly in the air efficiently. The flow around the wing is very sensitive to changes in the angle of attack. Beyond a value, there is a phenomenon of the boundary layer separation on the upper surface, which causes instability and total degradation of aerodynamic performance called a stall. However, controlling flow around an airfoil has become a researcher concern in the aeronautics field. There are two techniques for controlling flow around a wing to improve its aerodynamic performance: passive and active controls. Blowing and suction are among the active techniques that control the boundary layer separation around an airfoil. Their objective is to give energy to the air particles in the boundary layer separation zones and to create vortex structures that will homogenize the velocity near the wall and allow control. Blowing and suction have long been used as flow control actuators around obstacles. In 1904 Prandtl applied a permanent blowing to a cylinder to delay the boundary layer separation. In the present study, several numerical investigations have been developed to predict a turbulent flow around an aerodynamic profile. CFD code was used for several angles of attack in order to validate the present work with that of the literature in the case of a clean profile. The variation of the lift coefficient CL with the momentum coefficient

Keywords: CFD, control flow, lift, slot

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Authors: Fei Gao, Rodolfo C. Raga Jr.

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This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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Authors: A. Zeynolabedin, M. A. Olyaei, B. Ghiasi

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Drought is an inevitable part of the earth’s climate. It occurs regularly with no clear warning and without recognizing borders. In addition, its impact is cumulative and not immediately discernible. Iran is located in a semi-arid region where droughts occur periodically as natural hazard. Standardized Precipitation Index (SPI), Surface Water Supply Index (SWSI), and Palmer Drought Severity Index (PDSI) are three well-known indices which describe drought severity; each has its own advantages and disadvantages and can be used for specific types of drought. These indices take into account some factors such as precipitation, reservoir storage and discharge, temperature, and potential evapotranspiration in determining drought severity. In this paper, first all three indices are calculated in Aharchay river watershed located in northwestern part of Iran in East Azarbaijan province. Next, based on two other important parameters which are groundwater level and solar radiation, two new indices are defined. Finally, considering all five aforementioned indices, a combined drought index (CDI) is presented and calculated for the region. This combined index is based on all the meteorological, hydrological, and agricultural features of the region. The results show that the most severe drought condition in Aharchay watershed happened in Jun, 2004. The result of this study can be used for monitoring drought and prepare for the drought mitigation planning.

Keywords: drought, GIS, intensity index, regional assessment, variation maps

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Authors: H. Malachova, A. Oulehlova, D. Rezac

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Crisis preparedness training is the best possible strategy for identifying weak points, understanding vulnerability, and finding possible strategies for mitigation of blackout consequences. Training represents an effective tool for developing abilities and skills to cope with crisis situations. This article builds on the results of the research carried out in the field of preparation, realization, process, and impacts of training on subjects of energy sector critical infrastructure as a part of crisis preparedness. The research has revealed that the subjects of energy sector critical infrastructure have not realized training and therefore are not prepared for the restoration of the energy supply and black start after blackout regardless of the fact that most subjects state blackout and subsequent black start as key dangers. Training, together with mutual communication and processed crisis documentation, represent a basis for successful solutions for dealing with emergency situations. This text presents the suggested model of SIMEX simulator as a tool which supports managing crisis situations, containing training environment. Training models, possibilities of constructive simulation making use of non-aggregated as well as aggregated entities and tools of communication channels of individual simulator nodes have been introduced by the article.

Keywords: communication, energetic critical infrastructure, training, simulation

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Authors: Harunori Kawabe, Hideyuki Aoshima, Koji Murakami, Minoru Kawakami, Yuka Nakano, David D. Ordinario, C. W. Crawford, Iri Sato-Baran

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With the recent advances in gene editing technologies allowing the rewriting of genetic sequences, additional market growth in the global floriculture market beyond previous trends is anticipated through increasingly sophisticated plant breeding techniques. As a prerequisite for gene editing, the gene sequence of the target plant must first be identified. This necessitates the genetic analysis of plants with unknown gene sequences, the extraction of RNA, and comprehensive expression analysis. Consequently, a technology capable of consistently and effectively extracting high-purity DNA and RNA from plants is of paramount importance. Although model plants, such as Arabidopsis and tobacco, have established methods for DNA and RNA extraction, floricultural species such as roses present unique challenges. Different techniques to extract DNA and RNA from various floricultural species were investigated. Upon sampling and grinding the petals of several floricultural species, it was observed that nucleic acid extraction from the ground petal solutions of low viscosity was straightforward; solutions of high viscosity presented a significant challenge. It is postulated that the presence of substantial quantities of polysaccharides and polyphenols in the plant tissue was responsible for the inhibition of nucleic acid extraction. Consequently, attempts were made to extract high-purity DNA and RNA by improving the CTAB method and combining it with commercially available nucleic acid extraction kits. The quality of the total extracted DNA and RNA was evaluated using standard methods. Finally, the effectiveness of the extraction method was assessed by determining whether it was possible to create a library that could be applied as a suitable template for a next-generation sequencer. In conclusion, a method was developed for consistent and accurate nucleic acid extraction from high-viscosity floricultural samples. These results demonstrate improved techniques for DNA and RNA extraction from flowers, help facilitate gene editing of floricultural species and expand the boundaries of research and commercial opportunities.

Keywords: floriculture, gene editing, next-generation sequencing, nucleic acid extraction

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Authors: Victor Oyewumi Ogunbiyi

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Food waste is a global sustainability issue that demands that multiple stakeholders participate in solving it. This article examines how different food system stakeholders are held responsible in the policy debate related to food waste reduction. The study adopts a qualitative approach, paying attention to the views of both public and private policymakers and constructing their views relating to opportunities and policy initiatives towards waste reduction. The data consists of a list of opportunities and food policy initiatives in the development process in Nigeria. The authors identify three emerging opportunities: sectoral growth, technological demands in food service, and sustainable collaborative behaviour. The findings also revealed key policy initiatives for development: law and regulations, multi-stakeholder collaboration, economic incentives, research, and new knowledge. The study extends the marketing literature on food sustainability by investigating several stakeholders’ roles beyond the practical management of the food services sector. Additionally, considering policy initiative development for food waste mitigation sheds light on how stakeholders’ policy initiatives can sustain the food service sector. Finally, the authors outline policy implications.

Keywords: multistakeholder engagement, food services, food waste, policy initiatives, Nigeria

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Authors: J. Satya Eswari, Ch. Venkateswarlu

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The formulation of a commercial pharmaceutical product involves several composition factors and response characteristics. When the formulation requires to satisfy multiple response characteristics which are conflicting, an optimal solution requires the need for an efficient multiobjective optimization technique. In this work, a regression is combined with a non-dominated sorting differential evolution (NSDE) involving Naïve & Slow and ε constraint techniques to derive different multiobjective optimization strategies, which are then evaluated by means of a trapidil pharmaceutical formulation. The analysis of the results show the effectiveness of the strategy that combines the regression model and NSDE with the integration of both Naïve & Slow and ε constraint techniques for Pareto optimization of trapidil formulation. With this strategy, the optimal formulation at pH=6.8 is obtained with the decision variables of micro crystalline cellulose, hydroxypropyl methylcellulose and compression pressure. The corresponding response characteristics of rate constant and release order are also noted down. The comparison of these results with the experimental data and with those of other multiple regression model based multiobjective evolutionary optimization strategies signify the better performance for optimal trapidil formulation.

Keywords: pharmaceutical formulation, multiple regression model, response surface method, radial basis function network, differential evolution, multiobjective optimization

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Authors: M. A. Karakassides, M. Baikousi, A. Kouloumpis, D. Gournis

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Nanocomposites of Carbon Nanorods (CNRs) with Polystyrene (PS), have been synthesized successfully by means of in situ polymerization process and characterized. Firstly, carbon nanorods with graphitic structure were prepared by the standard synthetic procedure of CMK-3 using MCM-41 as template, instead of SBA-15, and sucrose as carbon source. In order to create an organophilic surface on CNRs, two parts of modification were realized: surface chemical oxidation (CNRs-ox) according to the Staudenmaier’s method and the attachment of octadecylamine molecules on the functional groups of CNRs-ox (CNRs-ODA The nanocomposite materials of polystyrene with CNRs-ODA, were prepared by a solution-precipitation method at three nanoadditive to polymer loadings (1, 3 and 5 wt. %). The as derived nanocomposites were studied with a combination of characterization and analytical techniques. Especially, Fourier-transform infrared (FT-IR) and Raman spectroscopies were used for the chemical and structural characterization of the pristine materials and the derived nanocomposites while the morphology of nanocomposites and the dispersion of the carbon nanorods were analyzed by atomic force and scanning electron microscopy techniques. Tensile testing and thermogravimetric analysis (TGA) along with differential scanning calorimetry (DSC) were also used to examine the mechanical properties and thermal stability -glass transition temperature of PS after the incorporation of CNRs-ODA nanorods. The results showed that the thermal and mechanical properties of the PS/ CNRs-ODA nanocomposites gradually improved with increasing of CNRs-ODA loading.

Keywords: nanocomposites, polystyrene, carbon, nanorods

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Authors: Mohamed A. Alhammad, Hadia A. Abou-Donia, Mona H. Hashish, Mohamed N. Massoud

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Background: Rotavirus is the leading etiologic agent of severe diarrheal disease in infants and young children worldwide. The present study was aimed 1) to detect rotavirus infection as a cause of diarrhoea among children under 5 years of age using the two serological methods (ELISA and LA) and the PCR technique (2) to evaluate the three methodologies used for human RV detection in stool samples. Materials and Methods: This study was carried out on 247 children less than 5 years old, diagnosed clinically as acute gastroenteritis and attending Alexandria University Children Hospital at EL-Shatby. Rotavirus antigen was screened by ELISA and LA tests in all stool samples, whereas only 100 samples were subjected to RT-PCR method for detection of rotavirus RNA. Results: Out of the 247 studied cases with diarrhoea, rotavirus antigen was detected in 83 (33.6%) by ELISA and 73 (29.6%) by LA, while the 100 cases tested by RT-PCR showed that 44% of them had rotavirus RNA. Rotavirus diarrhoea was significantly presented with a marked seasonal peak during autumn and winter (61.4%). Conclusion: The present study confirms the huge burden of rotavirus as a major cause of acute diarrhoea in Egyptian infants and young children. It was concluded that; LA is equal in sensitivity to ELISA, ELISA is more specific than LA, and RT-PCR is more specific than ELISA and LA in diagnosis of rotavirus infection.

Keywords: rotavirus, diarrhea, immunoenzyme techniques, latex fixation tests, RT-PCR

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Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay

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With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Keywords: Credit Card Fraud Detection, User Authentication, Behavioral Biometrics, Machine Learning, Literature Survey

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Authors: Hadi Ardiny, Amir Mohammad Beigzadeh

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Through the utilization of a combination of various sensors and data fusion methods, the detection of potential nuclear threats can be significantly enhanced by extracting more information from different data. In this research, an experimental and modeling approach was employed to track a radioactive source by combining a surveillance camera and a radiation detector (NaI). To run this experiment, three mobile robots were utilized, with one of them equipped with a radioactive source. An algorithm was developed in identifying the contaminated robot through correlation between camera images and camera data. The computer vision method extracts the movements of all robots in the XY plane coordinate system, and the detector system records the gamma-ray count. The position of the robots and the corresponding count of the moving source were modeled using the MCNPX simulation code while considering the experimental geometry. The results demonstrated a high level of accuracy in finding and locating the target in both the simulation model and experimental measurement. The modeling techniques prove to be valuable in designing different scenarios and intelligent systems before initiating any experiments.

Keywords: nuclear threats, radiation detector, MCNPX simulation, modeling techniques, intelligent systems

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Authors: M. Kang'ethe Simon, Nomngcoyiya Thanduxolo

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The aim of this article is to explore the role of selected cultural practices and assess how they can be a panacea in mitigating the state of social vices in South Africa. The article uses a review of literature methodology. Findings indicate that Africans were hoodwinked by white people to abandon their cultures for western based cultures. African cultures continue to weaken as they succumb to forces of westernization, eurocentrism, modernization, civilization, and globalization. Africans have realised that their cultures abandoned such as virginity testing, sexual mores and taboos and circumcision could be a panacea in mitigating some of the societal ills such as moral decadence and HIV/AIDS. The article urges for a resuscitation of cultural practices such as virginity testing, thigh sex (ukumetsha), circumcision and teachings that accompanied initiation schools; and societies to undergo an attitudinal and cultural paradigm shift that will consider the invaluable aspects of cultures that can effectuate and facilitate mitigation of social ills in African countries such as South Africa.

Keywords: virginity testing (reed dance), circumcision, initiation schools, African Renaissance, thigh sex, moral decadence, cultural custodians, state of anomie

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Authors: Venkata Ramana Pamu

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This paper is a case study of a 5310 ML capacity Raw Water Reservoir (RWR), situated in Indian state Rajasthan, which is a part of Rajasthan Rural Water Supply & Fluorosis Mitigation Project. This RWR embankment was constructed by locally available material on natural ground profile. Height of the embankment was varying from 2m to 10m.This is due to existing ground level was varying. Reservoir depth 9m including 1.5m free board and 1V:3H slopes were provided both upstream and downstream side. Proper soil investigation, tests were done and it was confirmed that the existing soil is sandy silt. The existing excavated earth was used as filling material for embankment construction, due to this controlling seepage from upstream to downstream be a challenging task. Slope stability and Seismic analysis of the embankment done by Conventional method for both full reservoir condition and rapid drawdown. Horizontal filter at toe level was provided along with upstream side PCC (Plain Cement Concrete) block and HDPE (High Density poly ethylene) lining as a remedy to control seepage. HDPE lining was also provided at storage area of the reservoir bed level. Mulching was done for downstream side slope protection.

Keywords: raw water reservoir, seepage, seismic analysis, slope stability

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Authors: Giovanni Menichini, Salvatore Giacomo Morano, Gloria Terenzi, Luca Salvatori, Maurizio Orlando

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The “Guidelines for Risk Classification, Safety Assessment, and Structural Health Monitoring of Existing Bridges” were recently approved by the Italian Government to define technical standards for managing the national network of existing bridges. These guidelines provide a framework for risk mitigation and safety assessment of bridges, which are essential elements of the built environment and form the basis for the operation of transport systems. Within the guideline framework, a workflow based on three main points was proposed: (1) risk-based, i.e., based on typical parameters of hazard, vulnerability, and exposure; (2) multi-level, i.e., including six assessment levels of increasing complexity; and (3) multirisk, i.e., assessing structural/foundational, seismic, hydrological, and landslide risks. The paper focuses on applying the Italian Guidelines to specific case studies, aiming to identify the parameters that predominantly influence the determination of the “class of attention”. The significance of each parameter is determined via sensitivity analysis. Additionally, recommendations for enhancing the process of assigning the class of attention are proposed.

Keywords: bridge safety assessment, Italian guidelines implementation, risk classification, structural health monitoring

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Authors: Seyed Hassan Moosa-kazemi, Jalal Mohammadi Soleimani, Hassan Vatandoost, Mohammad Hassan Shirazi, Sara Hajikhani, Roonak Bakhtiari, Morteza Akbari, Siamak Hydarzadeh

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Malaria is an infectious disease and considered most important health problems in the southeast of Iran. Iran is elimination malaria phase and new tool need to vector control. Paraterasgenesis is a new way to cut of life cycle of the malaria parasite. In this study, the microflora of the surface and gut of various stages of Anopheles fluviatilis James as one of the important malaria vector was studied using biochemical and molecular techniques during 2013-2014. Twelve bacteria species were found including; Providencia rettgeri, Morganella morganii, Enterobacter aerogenes, Pseudomonas oryzihabitans, Citrobacter braakii، Citrobacter freundii، Aeromonas hydrophila، Klebsiella oxytoca, Citrobacter koseri, Serratia fonticola، Enterobacter sakazakii and Yersinia pseudotuberculosis. The species of Alcaligenes faecalis, Providencia vermicola and Enterobacter hormaechei were identified in various stages of the vector and confirmed by biochemical and molecular techniques. We found Providencia rettgeri proper candidate for paratransgenesis.

Keywords: Anopheles fluviatilis, bacteria, malaria, Paraterasgenesis, Southern Iran

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Authors: Gyu-Dong Kim, Wuk-Jae Yoo, Sang-Youl Lee

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Composite structures offer numerous advantages over conventional structural systems in the form of higher specific stiffness and strength, lower life-cycle costs, and benefits such as easy installation and improved safety. Recently, there has been a considerable increase in the use of composites in engineering applications and as wraps for seismic upgrading and repairs. However, these composites deteriorate with time because of outdated materials, excessive use, repetitive loading, climatic conditions, manufacturing errors, and deficiencies in inspection methods. In particular, damaged fibers in a composite result in significant degradation of structural performance. In order to reduce the failure probability of composites in service, techniques to assess the condition of the composites to prevent continual growth of fiber damage are required. Condition assessment technology and nondestructive evaluation (NDE) techniques have provided various solutions for the safety of structures by means of detecting damage or defects from static or dynamic responses induced by external loading. A variety of techniques based on detecting the changes in static or dynamic behavior of isotropic structures has been developed in the last two decades. These methods, based on analytical approaches, are limited in their capabilities in dealing with complex systems, primarily because of their limitations in handling different loading and boundary conditions. Recently, investigators have introduced direct search methods based on metaheuristics techniques and artificial intelligence, such as genetic algorithms (GA), simulated annealing (SA) methods, and neural networks (NN), and have promisingly applied these methods to the field of structural identification. Among them, GAs attract our attention because they do not require a considerable amount of data in advance in dealing with complex problems and can make a global solution search possible as opposed to classical gradient-based optimization techniques. In this study, we propose an alternative damage-detection technique that can determine the degraded stiffness distribution of vibrating laminated composites made of Glass Fiber-reinforced Polymer (GFRP). The proposed method uses a modified form of the bivariate Gaussian distribution function to detect degraded stiffness characteristics. In addition, this study presents a method to detect the fiber property variation of laminated composite plates from the micromechanical point of view. The finite element model is used to study free vibrations of laminated composite plates for fiber stiffness degradation. In order to solve the inverse problem using the combined method, this study uses only first mode shapes in a structure for the measured frequency data. In particular, this study focuses on the effect of the interaction among various parameters, such as fiber angles, layup sequences, and damage distributions, on fiber-stiffness damage detection.

Keywords: stiffness detection, fiber damage, genetic algorithm, layup sequences

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Authors: James Hilton Williams

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Recent tsunami events, including the 2011 Tohoku Tsunami, Japan, and the 2015 Illapel Tsunami, Chile, have highlighted the potential for tsunami impacts on the built environment. International research in the tsunami impacts domain has been largely focused toward impacts on buildings and casualty estimations, while only limited attention has been placed on the impacts on infrastructure which is critical for the recovery of impacted communities. New Zealand, with 75% of the population within 10 km of the coast, has a large amount of coastal infrastructure exposed to local, regional and distant tsunami sources. To effectively manage tsunami risk for New Zealand critical infrastructure, including energy, transportation, and communications, the vulnerability of infrastructure networks and components must first be determined. This research develops infrastructure asset vulnerability, functionality and repair- cost functions based on international post-event tsunami impact assessment data from technologically similar countries, including Japan and Chile, and adapts these to New Zealand. These functions are then utilized within a New Zealand based impact framework, allowing for cost benefit analyses, effective tsunami risk management strategies and mitigation options for exposed critical infrastructure to be determined, which can also be applied internationally.

Keywords: impact assessment, infrastructure, tsunami impacts, vulnerability functions

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Authors: Noor Azwa Azreen Binti Abd. Aziz, Muhamad Zaim Bin Mohd Rozi

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Moving towards the 4th Industrial Revolution, artificial intelligence (AI) is now more popular than ever. This subject is gaining significance every day and is continually expanding, often merging with other fields. Instead of merely being passive observers, there are benefits to understanding modern technology by delving into its inner workings. However, in a world teeming with digital information, the impact of AI on the spread of disinformation has garnered significant attention. The dissemination of inaccurate or misleading information is referred to as misinformation, posing a serious threat to democratic society, public debate, and individual decision-making. This article delves deep into the connection between AI and the dissemination of false information, exploring its potential, risks, and ethical issues as AI technology advances. The rise of AI has ushered in a new era in the dissemination of misinformation as AI-driven technologies are increasingly responsible for curating, recommending, and amplifying information on online platforms. While AI holds the potential to enhance the detection and mitigation of misinformation through natural language processing and machine learning, it also raises concerns about the amplification and propagation of false information. AI-powered deepfake technology, for instance, can generate hyper-realistic videos and audio recordings, making it increasingly challenging to discern fact from fiction.

Keywords: artificial intelligence, digital information, disinformation, ethical issues, misinformation

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Authors: Sandani Muthukumarana, Malith Shehan Keraminiyage, Pavithra Rathnasiri

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Climate change is one of the most pressing issues facing our generation. However, it also presents an opportunity to grow the economy using biotechnology. Biotechnology offers a variety of solutions that can help mitigate the effects of global warming. Despite this, there is a lack of research on the potential and challenges associated with the further use of biotechnology to combat the impacts of climate change. To address this gap, it is essential to investigate the current context surrounding the use of biotechnology for climate change mitigation, including potential applications, current practices, and existing challenges. By reviewing the existing literature on these perspectives, this paper aims to provide a comprehensive understanding of the potential for biotechnology to mitigate the hazards of climate change. The use of biotechnology to mitigate the effects of climate change will be made easier as a result, and this will lay the groundwork for further study and actual initiatives in this field. Biotechnology can play a crucial role in mitigating the impacts of climate change. It offers a range of solutions, such as genetically modified crops, bioremediation, and bioenergy, that can help reduce greenhouse gas emissions, enhance carbon sequestration, and increase climate resilience. By utilizing biotechnology, we can reduce the negative impacts of climate change and create a more sustainable future. According to this knowledge, researchers can harness the potential of biotechnology to fight climate change and build a more sustainable future for future generations.

Keywords: biotechnology, impact, solutions, climate changes

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Authors: Chokri Slim

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The objective of this research is attempting to respond to this question: Is there a significant difference between the regression model and statistical learning models in predicting credit risk management? A Multiple Linear Regression (MLR) model was compared with neural networks including Multi-Layer Perceptron (MLP), and a Support vector regression (SVR). The population of this study includes 50 listed Banks in Tunis Stock Exchange (TSE) market from 2000 to 2016. Firstly, we show the factors that have significant effect on the quality of loan portfolios of banks in Tunisia. Secondly, it attempts to establish that the systematic use of objective techniques and methods designed to apprehend and assess risk when considering applications for granting credit, has a positive effect on the quality of loan portfolios of banks and their future collectability. Finally, we will try to show that the bank governance has an impact on the choice of methods and techniques for analyzing and measuring the risks inherent in the banking business, including the risk of non-repayment. The results of empirical tests confirm our claims.

Keywords: credit risk management, multiple linear regression, principal components analysis, artificial neural networks, support vector machines

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Authors: Zohre Soleymani, Meisam Amirzadeh

Abstract:

Many products are safety critical, so proactive analysis techniques are vital for them because these techniques try to identify potential failures before the products are produced. Failure Mode and Effective Analysis (FMEA) is an effective tool in identifying probable problems of product or process and prioritizing them and planning for its elimination. The paper shows the implementation of FMEA process to identify and remove potential troubles of aero fuel pumps manufacturing process and improve the reliability of subsystems. So the different possible causes of failure and its effects along with the recommended actions are discussed. FMEA uses Risk Priority Number (RPN) to determine the risk level. RPN value is depending on Severity(S), Occurrence (O) and Detection (D) parameters, so these parameters need to be determined. After calculating the RPN for identified potential failure modes, the corrective actions are defined to reduce risk level according to assessment strategy and determined acceptable risk level. Then FMEA process is performed again and RPN revised is calculated. The represented results are applied in the format of a case study. These results show the improvement in manufacturing process and considerable reduction in aero fuel pump production risk level.

Keywords: FMEA, risk priority number, aero pump, corrective action

Procedia PDF Downloads 288

Authors: Liseane Padilha Thives, Mayara S. S. Lima, João Victor Staub De Melo, Glicério Trichês

Abstract:

Red mud is a waste resulting from the processing of bauxite to alumina, the raw material of the production of aluminum. The large quantity of red mud generated and inadequately disposed in the environment has motivated researchers to develop methods for reinsertion of this waste into the productive cycle. This work aims to evaluate the resistance to permanent deformation of dense asphalt mixtures with red mud filler. The red mud was characterized by tests of X-ray diffraction, fluorescence, specific mass, laser granulometry, pH and scanning electron microscopy. For the analysis of the influence of the quantity of red mud in the mechanical performance of asphalt mixtures, a total filler content of 7% was established. Asphalt mixtures with 3%, 5% and 7% red mud were produced. A conventional mixture with 7% stone powder filler was used as reference. The asphalt mixtures were evaluated for performance to permanent deformation in the French Rutting Tester (FRT) traffic simulator. The mixture with 5% red mud presented greater resistance to permanent deformation with rutting depth at 30,000 cycles of 3.50%. The asphalt mixtures with red mud presented better performance, with reduction of the rutting of 12.63 to 42.62% in relation to the reference mixture. This study confirmed the viability of reinserting the red mud in the production chain and possible usage in the construction industry. The red mud as filler in asphalt mixtures is a reuse option of this waste and mitigation of the disposal problems, as well as being an environmentally friendly alternative.

Keywords: asphalt mixtures, permanent deformation, red mud, pavements

Procedia PDF Downloads 293

Authors: Stuti Modi, Aditi Kambli

Abstract:

This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.

Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution

Procedia PDF Downloads 191

Authors: Mohammed Sale Abubakar, Kabir Omar, Mohammed Umar Abba

Abstract:

The effects of climate change continue to ravage globe upsetting or even overturning the entire communities in its wake. It is therefore on the front burner of most global issues affecting the world today. Hardly any field of endeavor has escaped the manifestation of its effects. The effects of climate change on agricultural productivity calls for intense study because of the nexus between agriculture, global food security and provision of employment for the teaming population in sub-saharan Africa. This paper examines current challenges of climate change on agricultural productivity in this region. This challenge indicated that both long and short-term change in climate bring unpleasant repercussion on agricultural productivity as they manifest in the vulnerability of industrial work force. The paper also focused on the impact of agriculture and bio-environmental engineering as a separate entity that will help to fight these major challenges facing humanity currently associated with negative effects of climate change such as scarcity of water, declining agricultural yields, desert encroachment, and damage of coastal structures. Finally, a suggestion was put forward as an effort that should be directed towards mitigating the negative effects of climate change on our environment.

Keywords: climate change mitigation, desert encroachment, environment, global food security, greenhouse gases (GHGs)

Procedia PDF Downloads 360

Authors: Gaddafi Sani Shehu, Tankut Yalcınoz, Abdullahi Bala Kunya

Abstract:

Multilevel inverters such as flying capacitor, diode-clamped, and cascaded H-bridge inverters are very popular particularly in medium and high power applications. This paper focuses on a cascaded H-bridge module using a single direct current (DC) source in order to generate an 11-level output voltage. The noble approach reduces the number of switches and gate drivers, in comparison with a conventional method. The anticipated topology produces more accurate result with an isolation transformer at high switching frequency. Different modulation techniques can be used for the multilevel inverter, but this work features modulation techniques known as selective harmonic elimination (SHE).This modulation approach reduces the number of carriers with reduction in Switching Losses, Total Harmonic Distortion (THD), and thereby increasing Power Quality (PQ). Based on the simulation result obtained, it appears SHE has the ability to eliminate selected harmonics by chopping off the fundamental output component. The performance evaluation of the proposed cascaded multilevel inverter is performed using PSIM simulation package and THD of 0.94% is obtained.

Keywords: cascaded H-bridge multilevel inverter, power quality, selective harmonic elimination

Procedia PDF Downloads 423